use "$path\datasets\rd_dataset.dta", clear

sort gkz jahr
merge m:1 gkz jahr  using "$path/datasets/minutes_data.dta"
keep if _merge==3




local depvar "top_bu_church"
bandwidth_and_weights, depvar(`depvar') var(margin_1)  bwmethod(CCT) kernel(tri) degree(1) number_of_elec(num_of_obs)
ivreg2 `depvar' elected_women margin_1 inter_1   if abs(margin_1)<$bw_opt  [pw=weight] , r cluster(gkz ) partial(margin_1 inter_1 )
est store m1
estadd local bw "CCT"
estadd local degree "Linear"
estadd local bw_length  $bw_opt
unique gkz_legis_party if e(sample)
estadd local num_of_elections  `"`r(sum)'"'
sum `depvar' if e(sample)
estadd scalar  mean_depvar =r(mean)
estadd scalar sd_depvar =r(sd)


local depvar "top_bu_utilitie"
bandwidth_and_weights, depvar(`depvar') var(margin_1)  bwmethod(CCT) kernel(tri) degree(1) number_of_elec(num_of_obs)
ivreg2 `depvar' elected_women margin_1 inter_1   if abs(margin_1)<$bw_opt  [pw=weight] , r cluster(gkz ) partial(margin_1 inter_1 )
est store m2
estadd local bw "CCT"
estadd local degree "Linear"
estadd local bw_length  $bw_opt
unique gkz_legis_party if e(sample)
estadd local num_of_elections  `"`r(sum)'"'
sum `depvar' if e(sample)
estadd scalar  mean_depvar =r(mean)
estadd scalar sd_depvar =r(sd)


local depvar "top_bu_roadsecu"
bandwidth_and_weights, depvar(`depvar') var(margin_1)  bwmethod(CCT) kernel(tri) degree(1) number_of_elec(num_of_obs)
ivreg2 `depvar' elected_women margin_1 inter_1   if abs(margin_1)<$bw_opt  [pw=weight] , r cluster(gkz ) partial(margin_1 inter_1 )
est store m3
estadd local bw "CCT"
estadd local degree "Linear"
estadd local bw_length  $bw_opt
unique gkz_legis_party if e(sample)
estadd local num_of_elections  `"`r(sum)'"'
sum `depvar' if e(sample)
estadd scalar  mean_depvar =r(mean)
estadd scalar sd_depvar =r(sd)


local depvar "top_bu_sewagedi"
bandwidth_and_weights, depvar(`depvar') var(margin_1)  bwmethod(CCT) kernel(tri) degree(1) number_of_elec(num_of_obs)
ivreg2 `depvar' elected_women margin_1 inter_1   if abs(margin_1)<$bw_opt  [pw=weight] , r cluster(gkz ) partial(margin_1 inter_1 )
est store m4
estadd local bw "CCT"
estadd local degree "Linear"
estadd local bw_length  $bw_opt
unique gkz_legis_party if e(sample)
estadd local num_of_elections  `"`r(sum)'"'
sum `depvar' if e(sample)
estadd scalar  mean_depvar =r(mean)
estadd scalar sd_depvar =r(sd)


local depvar "top_bu_streetcl"
bandwidth_and_weights, depvar(`depvar') var(margin_1)  bwmethod(CCT) kernel(tri) degree(1) number_of_elec(num_of_obs)
ivreg2 `depvar' elected_women margin_1 inter_1   if abs(margin_1)<$bw_opt  [pw=weight] , r cluster(gkz ) partial(margin_1 inter_1 )
est store m5
estadd local bw "CCT"
estadd local degree "Linear"
estadd local bw_length  $bw_opt
unique gkz_legis_party if e(sample)
estadd local num_of_elections  `"`r(sum)'"'
sum `depvar' if e(sample)
estadd scalar  mean_depvar =r(mean)
estadd scalar sd_depvar =r(sd)




************************************************************************************************************************************



esttab  m1 m2 m3 m4 m5 using TableA30/tableA30.txt, style(tab) replace order( ) mlabel(,none) ///
cells(b(label(coef.) star fmt(%8.3f) ) se(label((z)) par fmt(%6.3f))) ///
collabels(none) ///
keep (elected_women  ) ///
stats(bw bw_length degree N   N_clust mean_depvar sd_depvar , layout( @ @ @ @ @  `""@ (@)""' )  fmt( %~#s %9.2f %~# %9.0g %9.0g  %9.2f %9.2f  ) ///
labels("Bandwidth type" "Bandwidth size" "Polynomial"   "N"  "Municipalities" "Mean (SD)"  )) ///
starlevels(* 0.10 ** 0.05 *** 0.01) ///
varlabels( elected_women "Female victory"   ) 


